IBM Big Data Hub

SEPTEMBER 13, 2023

Incorporating an effective attack surface management tool into your security strategy can significantly help you mitigate the risks of data breaches. Because hackers don’t limit their reconnaissance efforts to what’s in your inventory, these unknown assets put you at risk.

Risk 96

Risk Management Strategy Measurement 96

Cloudera

MARCH 2, 2022

Risk management is a highly dynamic discipline these days. Stress testing is a particular area that has become even more important throughout the pandemic. Similarly, the European Central Bank is issuing stress testing requirements related to climate risk given the potential economic shifts related to addressing climate change.

Testing 93

Testing Management Risk Management Forecasting 93

DataRobot Blog

APRIL 29, 2022

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111

Risk Modeling IT Risk Management 111

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . Area such as: .

Risk 99

Risk Optimization Management Insurance 99

Cloudera

OCTOBER 20, 2021

As part of these efforts, disclosure requirements will mandate that firms provide “the impact of a company’s activities on the environment and society, as well as the business and financial risks faced by a company due to its sustainability exposures.” What are the key climate risk measurements and impacts? They need to understand;

Risk 80

Risk Modeling Risk Management Measurement 80

DataKitchen

MARCH 12, 2024

We kept adding tests over time; it has been several years since we’ve had any major glitches. Our vision was to create a flexible, state-of-the-art data infrastructure that would allow our analysts to transform the data rapidly with a very low risk of error. Data errors can cause compliance risks. That was amazing for the team.”

Metrics 117

Metrics Software Cost-Benefit Testing 117

Sisense

SEPTEMBER 23, 2019

If it breaks, it puts at risk, not just a single application, but an entire chain of business processes built around it. If it breaks, it puts at risk, not just a single application, but an entire chain of business processes built around it. So the importance of API testing is obvious. Image source: Martin Fowler.

Testing 89

Testing Strategy Modeling ROI 89

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform. End-to-end Data Lifecycle.

Risk 88

Risk Marketing Technology Management 88

IBM Big Data Hub

MAY 13, 2024

This blog series demystifies enterprise generative AI (gen AI) for business and technology leaders. In the previous blog , we discussed the differentiated approach by IBM to delivering enterprise-grade models. Mitigate risks : Relying on a single model or a limited selection can be risky.

Modeling 71

Modeling Cost-Benefit Risk Testing 71

DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52

Risk Modeling Metrics Business Objectives 52

Laminar Security

JUNE 29, 2023

Using a risk-based approach to deal with policy violations and continuous compliance monitoring will help avoid data exposures and fines. Organizations risk significantly increasing public cloud data risks if they don’t take necessary steps to improve its security. Public cloud spending and adoption is growing fast.

Risk 52

Risk Big Data Testing Management 52

Cloudera

MARCH 28, 2019

The trouble is, mortgage lenders persist in relying on historical macro-economic assumptions in their models so they risk repeating the errors of a decade ago when banks – and their regulators – failed to recognize the warning signs from a far richer source: low-level micro-economic data. Risk management 3.0.

Risk 73

Risk Management Risk Management Machine Learning 73

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management. What Is Model Risk?

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Cloudera

MAY 18, 2021

These interactions are captured and the resulting synthetic data sets can be analysed for a number of applications, such as training models to detect emergent fraudulent behavior, or exploring “what-if” scenarios for risk management. Value-at-Risk (VaR) is a widely used metric in risk management. Intraday VaR. Citations. [1]

Risk 96

Risk Marketing Risk Management Data-driven 96

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. We’re not encouraging skepticism or fear, but companies should start AI products with a clear understanding of the risks, especially those risks that are specific to AI.

Enterprise 267

Enterprise Modeling Testing Reporting 267

IBM Big Data Hub

MARCH 22, 2024

However, various challenges arise in the QA domain that affect test case inventory, test case automation and defect volume. Managing test case inventory can become problematic due to the sheer volume of cases, which lead to inefficiencies and resource constraints.

Testing 76

Testing Optimization Software Risk 76

Decision Management Solutions

APRIL 23, 2019

In February, we published a blog post on “Using Technology to Add Value in Insurance”. in which he states there are only three levers of value in insurance: Sell More, Manage Risk Better (aka underwriting and adjusting), and Cost Less to Operate. Let’s dive into greater detail on the second lever – Manage Risk Better.

Insurance 69

Insurance Risk Technology Management 69

Aryng

APRIL 22, 2022

Most managers are good at formulating innovative […] The post How to differentiate the thin line separating innovation and risk in experimentation appeared first on Aryng's Blog. We have seen this as a general trend in start-ups, and we know that it’s an awful feeling!

Experimentation 52

Experimentation Risk Management IT 52

DataKitchen

FEBRUARY 21, 2023

Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” Still, there is little testing and no consistent deployment processes, and everyone is very busy with ‘keeping the lights on’ by constantly chasing down errors in production systems.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

DataKitchen

FEBRUARY 2, 2023

This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. Enterprises are more challenged than ever in their data sprawl , so reducing risk and lowering costs drive software spending decisions. What will exist at the end of 2025?

Metadata 130

Metadata Testing Risk Data Science 130

DataRobot Blog

JUNE 3, 2022

To understand the capabilities and address the risks of AI, all of us – developers, policy-makers, end-users, bystanders – must have a shared understanding of what AI is, how it can be applied to the benefit of humanity, and the risks involved when implementing it without guardrails in place to mitigate bias and harm. Download now.

Risk 52

Risk Predictive Modeling Modeling Technology 52

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? Keep it agile, with short design, develop, test, release, and feedback cycles: keep it lean, and build on incremental changes. Test early and often. Test and refine the chatbot.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

DataKitchen

DECEMBER 6, 2022

T est Automation : Business rules validation, test scripts management, test data management. We tell all our prospects to strive for zero errors and make deployment fast/low risk, and your team will see incredible gains in the amount of work they create. Industry analysts, in turn, both listen to and influence buyers.

Software 130

Software Marketing Data Lake Testing 130

Cloudera

APRIL 18, 2024

In the financial sector, regulations are essential for financial institutions to maintain stability by preventing excessive risk-taking, ensuring adequate capitalization and reducing the likelihood of failures or financial crises.

Risk Management 76

Risk Management Risk Testing Management 76

CIO Business Intelligence

MAY 3, 2024

During pilot testing, UPS earned 50% reduction in the time agents spent resolving e-mails. Firms are very concerned that without applying genAI to customer-facing apps, they are at high risk of disruption.” Gownder, in a blog post last November as UPS was putting its solution into limited production.

Testing 135

Testing Sales Enterprise Digital Transformation 135

Sisense

MARCH 3, 2021

This includes their medical diagnoses, prescriptions, allergies, and test results. Big data in healthcare has the power to improve care, lower costs, and save lives. Healthcare providers are steadily digitizing their internal operations, resulting in mountains of new data being collected daily.

Big Data 98

Big Data Risk Sales Insurance 98

IBM Big Data Hub

FEBRUARY 1, 2024

To help prepare, many organizations are testing their incident response (IR) plans and teams with cyber range simulations. million in data breach costs compared to organizations without an IR team or IR plan testing. Cybersecurity awareness and training Many companies struggle to understand their cyber risk.

Testing 87

Testing Data Processing Risk Consulting 87

Cloudera

OCTOBER 18, 2023

In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement — to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation. Debugging: Identifying and fixing bugs in code is essential for application security.

Cost-Benefit 78

Cost-Benefit Testing Machine Learning Optimization 78

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

IBM Big Data Hub

NOVEMBER 6, 2023

It’s at these endpoints that company and user data is vulnerable to various types of attacks and security risks, including: Authentication-based attacks : where hackers try to guess or steal user passwords or exploit weak authentication processes to gain access to API servers. Security testing.

Optimization 115

Optimization Testing Software Risk 115

DataKitchen

NOVEMBER 20, 2021

A DataOps Engineer can make test data available on demand. We have automated testing and a system for exception reporting, where tests identify issues that need to be addressed. It then autogenerates QC tests based on those rules. Every time we see an error, we address it with a new automated test.

Testing 246

Testing Machine Learning Data Warehouse Reporting 246

IBM Big Data Hub

JANUARY 19, 2024

Enterprises without disaster recovery strategies in place are risking costs and penalties that could far outweigh the money saved by not investing in the solution. Step 2: Perform a risk analysis Threats vary greatly depending on your industry and the type of business you run. million—a 15% increase over the last 3 years.

Strategy 92

Strategy Cost-Benefit Testing Risk 92

IBM Big Data Hub

MAY 24, 2024

This reduces the risk of errors and miscommunications, which can lead to significant losses in the financial industry. This will help identify issues early, reducing the risk of disruptions to the system. Test and validate messages regularly to ensure that they are formatted correctly and that the information is accurate.

Measurement 90

Measurement Software Marketing Risk 90

CIO Business Intelligence

MARCH 3, 2024

And only 45 percent of CISOs were very or somewhat concerned about the risks of unsecured printers, compared to 72 percent of CIOs. Quocirca said this disconnect between the views of CIOs and CISOs on print security could prevent companies from determining the true level of risk. Doing penetration testing. Using zero trust.

IT 94

IT Measurement Risk Testing 94

Domino Data Lab

AUGUST 6, 2021

All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. The primary focus of model governance involves tracking, testing and auditing. First is the data the model is using.

Machine Learning 145

Machine Learning Modeling Testing Risk 145

DataKitchen

AUGUST 8, 2023

It can improve data quality, mitigate risk and adhere to governance requirements, detect unexpected or unknown events, reduce time to investigate and solve issues, improve budget planning and cost control, and increase efficiency and productivity. However, there are potential risks and challenges in adopting Data Observability.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

datapine

OCTOBER 21, 2020

If you put on too many workers, you run the risk of having unnecessary labor costs add up. Every patient has his own digital record which includes demographics, medical history, allergies, laboratory test results, etc. All this vital information can be coupled with other trackable data to identify potential health risks lurking.

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364